JP7251911B2 - Dynamic coating thickness measurement and control - Google Patents

Description

TECHNICAL FIELD This disclosure relates generally to coating thickness measurement, and more particularly to systems and methods for dynamic coating thickness measurement and control.

The procedure for measuring current coating thickness is performed after the coating material has cured. Depending on the type of material, curing can take several hours. If the cured coating thickness does not match the desired coating thickness, the coating must be polished or reapplied, which may require another thickness measurement and additional curing time.

There is a need to reduce or eliminate the inconveniences and problems associated with measuring coating thickness.

In one embodiment, the system includes a robot, a sprayer coupled to the robot and operable to spray material at a first flow rate onto a substrate for a first predetermined number of passes; and a measuring device operable to measure one or more properties of the sprayed material while the material is wet. The system determines the thickness of the wet material based on one or more measured properties, and determines the thickness of the wet material required to obtain a certain cured thickness of the material within a second predetermined number of passes. It further includes an analyzer operable to calculate two flow rates. The calculated second flow rate is the first predetermined number of passes, the expected thickness of the wet material for one pass of the first predetermined number of passes, the specified thickness of the wet material, and the first flow rate. based on.

In some embodiments, the method comprises: spraying material at a first flow rate onto a substrate for a first predetermined number of passes with a sprayer coupled to a robot; and measuring one or more properties of the material while the material is wet. The method includes determining, by the analyzer, a thickness of the wet material based on the one or more measured properties; calculating a second flow rate required to obtain a cured thickness of . The calculated second flow rate is the first predetermined number of passes, the expected thickness of the wet material for one pass of the first predetermined number of passes, the specified thickness of the wet material, and the first flow rate. based on.

In certain embodiments, an apparatus includes a robot and a sprayer coupled to the robot and operable to spray material at a first flow rate onto a substrate for a first predetermined number of passes. The apparatus includes one or more computer processors configured to access data captured by the measurement device. The data includes one or more properties of the material sprayed onto the substrate by the sprayer during a first predetermined number of passes while the material is wet, the data includes captured by the measuring device during The one or more computer processors determine the thickness of the wet material based on the one or more measured properties to obtain a cured thickness of the material within a second predetermined number of passes. is configured to calculate a second flow rate required for The calculated second flow rate is the first predetermined number of passes, the expected thickness of the wet material for one pass of the first predetermined number of passes, the specified thickness of the wet material, and the first flow rate. based on.

Technical advantages of some embodiments of the present disclosure include determining the thickness of a wet material sprayed onto a substrate, rather than waiting for the material to harden, thereby allowing in-process measurements becomes possible. Another advantage of some embodiments includes measuring one or more properties of a material sprayed onto a substrate without contacting the wet material, thereby allowing non-destructive measurements.

Another advantage of certain embodiments is that the material flow rate can be adjusted during the spraying process to reduce or eliminate inaccuracies in the cured thickness of the material, thereby saving time and resources. can do. For example, if the measured coating thickness at a particular point during the coating process is thicker than the expected coating thickness, the flow rate can be reduced at a particular point during the coating process, thereby resulting in Eliminates the need to polish the coating. As another example, if the measured coating thickness at a particular point during the coating process is less than the expected coating thickness, the flow rate can be increased at a particular point during the coating process, thereby increasing the coating Eliminates the need to apply additional coatings after curing.

Other technical advantages will be readily apparent to one skilled in the art from the following drawings, descriptions, and claims. Moreover, although certain advantages have been listed above, various embodiments may include all, some, or none of the listed advantages.

For a more complete understanding of the present disclosure and its advantages, reference is made to the following description in conjunction with the accompanying drawings.

1 illustrates a system for regulating material flow, according to certain embodiments. 4 illustrates a method for regulating material flow, according to certain embodiments. 2 illustrates a computer system that can be used in the system of FIG. 1, according to certain embodiments;

To facilitate a better understanding of this disclosure, the following examples of specific embodiments are provided. The following examples should not be construed to limit or define the scope of this disclosure. Embodiments of the present disclosure and their advantages are best understood with reference to FIGS. 1-3, in which like reference numerals are used to indicate like and corresponding elements.

In manufacturing, coating thickness is generally measured after the coating material applied to the surface has cured. For example, flakes of the coating may flake off after the coating cures, and a micrometer can be used to mechanically measure flake thickness of the coating. In another example, an eddy current device (eg, a Fischerscope®) can be physically applied after curing of the coating to measure coating thickness using an electrical signal. Depending on the type of material, curing may take several hours. Also, if the measured coating thickness does not match the desired coating thickness, the coating must be polished or reapplied, requiring additional curing time and measurements.

To reduce or eliminate the above or other problems, some embodiments of the present disclosure identify the thickness of the wet material sprayed onto the substrate rather than waiting for the material to harden. which allows for in-process measurement and efficiency. Another advantage of some embodiments includes measuring one or more properties of a material sprayed onto a substrate without contacting the wet material, thereby allowing non-destructive measurements.

Another advantage of certain embodiments is that the material flow rate can be adjusted during the spraying process to reduce or eliminate inaccuracies in the cured thickness of the material, thereby saving time and resources. can do. For example, if the measured coating thickness at a particular point during the coating process is thicker than the expected coating thickness, the flow rate can be reduced at a particular point during the coating process, thereby resulting in Eliminates the need to polish the coating. As another example, if the measured coating thickness at a particular point during the coating process is less than the expected coating thickness, the flow rate can be increased at a particular point during the coating process, thereby increasing the coating Eliminates the need to apply additional coatings after curing.

Other technical advantages should be readily apparent to one of ordinary skill in the art from the following drawings, specification and claims. Furthermore, although certain advantages have been listed above, various embodiments may include all, some, or none of the listed advantages. Figures 1-3 provide additional details regarding systems and methods for dynamic coating thickness measurement and control.

FIG. 1 shows a system 100 for regulating the flow rate of material 110, according to certain embodiments. As shown in FIG. 1, system 100 may include robot 120, sprayer 130, measuring device 140, analyzer 150, coating delivery system 160, and human machine interface (HMI) 170. As shown in FIG.

Robot 120 is any machine capable of automatically performing one or more functions. In certain embodiments, robot 120 can be programmed by one or more computer systems (eg, computer system 300 ) to spray material 110 onto substrate 180 . Material 110 is any material that can be sprayed onto substrate 180 . For example, material 110 can be a liquid (eg, paint). As another example, material 110 can be a mixture of gas and liquid (eg, foam). Substrate 180 is any substrate to which material 110 can be sprayed. For example, substrate 180 can be a surface of a manufactured part.

In certain embodiments, robot 120 is programmed to spray material 110 onto substrate 180 in a predetermined number of passes. For example, robot 120 may be programmed to spray material 110 over substrate 180 in ten passes. In some embodiments, robot 120 is programmed to wait a predetermined amount of time between each pass. As an example, robot 120 may be programmed to wait 10 minutes between each pass. The waiting time between each pass can be fixed or variable.

System 100 may include one or more sprayers 130 . Sprayer 130 is any device capable of spraying material 110 onto substrate 180 . For example, the sprayer 130 can be a conventional high pressure sprayer 130 or a high volume low pressure sprayer 130 . In certain embodiments, sprayer 130 is a spray gun. As shown in the embodiment of FIG. 1, sprayer 130 can be coupled to robot 120 . For example, the spray gun 130 can be integrated with the robot 120 and the spray gun 130 is permanently attached to the robot 120 . As another example, the spray gun 130 can be fixed to the robot 120 and the spray gun 130 can be easily removed from and reattached to the robot 120 . In general, sprayer 130 may be positioned in any suitable manner to spray material 110 onto substrate 180 .

In certain embodiments, sprayer 130 can spray material 110 in a predetermined number of passes. Multiple passes may be required to prevent surface finish problems. For example, a thick paint film in one pass can result in orange peel, porosity, solvent bubbles, and the like. In some embodiments, the spray gun 130 waits a predetermined amount of time (ie, flash time) between each coat before overcoating the previous pass with the next pass. As an example, sprayer 130 sprays a first pass of material 110 onto substrate 180 , waits for a predetermined flash time, and then sprays a second pass of material 110 onto substrate 180 to produce a Resulting in a two-layer coating. Similarly, sprayer 130 may wait a predetermined flash time after spraying material 110 in a second pass onto substrate 180 and before spraying substrate 180 in a third pass.

In some embodiments, sprayer 130 can spray in one or more passes (eg, a first predetermined number of passes) with a first flow rate. The flow rate can be selected to achieve the expected coating thickness of material 110 . For example, the first flow rate may be selected to achieve an expected coating thickness of 1 mil (ie, one thousandth of an inch (0.0254 mm)) after one pass. As another example, the first flow rate may be selected to achieve an expected coating thickness of 10 mils (0.254 mm) after 10 passes.

Sprayer 130 of system 100 can regulate the flow rate of material 110 dispensed from sprayer 130 . In certain embodiments, sprayer 130 can be programmed by a computer system (eg, by computer system 300) to adjust a first flow rate of material 110 to a second flow rate of material 110. For example, sprayer 130 can be programmed to adjust a first flow rate of 150 cubic centimeters per minute (cc/min) to a second flow rate of 250 cc/min. In certain embodiments, sprayer 130 adjusts the flow rate by adjusting its plume shape and/or air pressure.

Measurement device 140 of system 100 is any device capable of measuring one or more properties of material 110 sprayed onto substrate 180 . In certain embodiments, measuring device 140 measures one or more properties of material 110 while material 110 is wet. For example, the measurement device 140 can measure the thickness of paint sprayed onto the production part while the paint is wet. In some embodiments, measurement device 140 measures one or more properties of material 110 without physically contacting material 110 . Measurement device 140 may measure one or more properties of material 110 during one or more flash times between each spray pass.

As shown in the embodiment of FIG. 1, measurement device 140 can be coupled to robot 120 . For example, the measuring device 140 can be integral with the robot 120 , with the measuring device 140 permanently attached to the robot 120 . As another example, the measuring device 140 can be fixed to the robot 120 and the measuring device 140 can be easily removed from and reattached to the robot 120 . In general, measuring device 140 may be positioned in any suitable manner to measure material 110 sprayed onto substrate 180 .

In certain embodiments, measurement device 140 is a probe (eg, microwave probe) that measures one or more electrical properties of material 110 . For example, the measurement device 140 can measure electrical performance data, such as the reflectivity of the construction material 110 for a particular frequency band, which is the coating thickness of the construction material (e.g., paint). is too thick, too thin, or of the correct thickness.

In certain embodiments, measurement device 140 is a sensor (eg, a terahertz sensor). For example, measurement device 140 may probe material 110 using short pulses of terahertz radiation. As another example, measurement device 140 may determine the thickness of material 110 (eg, coating thickness) using time-of-flight calculations. Time-of-flight calculations can be based on the time it takes for a pulse to propagate to and from material 110 .

Analyzer 150 of system 100 can be a processor, such as processor 302 described below with reference to FIG. In certain embodiments, analyzer 150 may determine the thickness of material 110 based on one or more properties measured by measurement device 140 . For example, analyzer 150 may use reflectance data received from a microwave probe to determine coating thickness of material 110 . As another example, analyzer 150 may determine the coating thickness of material 110 using time-of-flight measurements received from terahertz sensors.

In some embodiments, the analyzer 150 calculates the adjusted flow rate required to achieve a certain cure thickness within a given number of passes. If the measured coating thickness is not equal to the expected coating thickness, the first flow rate should be adjusted. The actual coating thickness can differ from the expected coating thickness due to variations in temperature, humidity, the working material itself, and the like.

Coating thickness can be expressed in any suitable unit of measure. For example, actual coating thickness and expected coating thickness can be expressed in mils. As another example, actual coating thickness and expected coating thickness can be expressed in millimeters. In yet another example, actual coating thickness and expected coating thickness can be expressed using arbitrary units (ie, relative units of measure).

The adjusted flow rate is based on a first predetermined number of passes, an expected thickness of the wet material 110 for one pass of the first predetermined number of passes, and one or more properties of the wet material 110 measured by the measuring device 140. It can be calculated based on the specified thickness and the first flow rate. In a specific embodiment, the formula for adjusted flow is:
F _n+1 =(t _n+1 /t _n )·F _n (Formula 1)
here,
F _n+1 : Adjusted flow rate F _n : Current pass flow rate t _n+1 : Expected thickness t _n : Measured thickness.

In certain embodiments, the expected thickness t _n+1 can be represented by the number of spray passes multiplied by the expected thickness of each layer of material 110 . Equation 1 can thus be expressed as follows.
F _n+1 =[(n·t ₁ )/t _n ]·F _n (Formula 2)
here,
n: number of passes t ₁ : individual expected thickness.

For example, a stiffener thickness of 10 mils (0.254 mm) is required after 10 passes. The first flow rate F _n is expected to produce a thickness t ₁ of 1 mil (0.0254 mm) per blow pass. After three passes, the measured thickness t _n is 3.5 mils (0.0889 mm) and the analyzer 150 can adjust the first flow rate by the following magnitude for the remaining passes: .
_F4 =[(n· _t1 )/ _tn ]· _F3
F4 = [(3·1 mil)/3.5 mil]· _F3
F4 = _0.86F3

In the above example, the measured coating thickness of material 110 exceeds the expected thickness by 0.5 mils (0.0127 mm), so the first flow rate is a low _F4 = 0.86 _F3 for the remaining passes. The flow will be adjusted to finally achieve 10 mils. The flow rate can remain at F ₄ =0.86 F ₃ as long as the expected (ie, desired) thickness of material 110 matches the measured thickness.

Similarly, if the measured thickness _tn of material 110 after five spray passes is 4.5 mils (0.1143 mm), analyzer 150 scales the second flow rate for the remaining passes to: can be adjusted.
_F6 =[(n· _t1 )/ _tn ]· _F5
F6 = [(5·1 mil)/4.5 mil]·F5
_F6 = 1.11 _F5

Since the measured coating thickness is only 0.5 mils (0.0127 mm) below the desired thickness, the fifth pass flow rate is _F6 for the remaining passes (i.e., passes 6, 7, and so on). = 1.11 F ₅ and finally achieves 10 mils (0.254 mm). The flow rate can remain at F ₆ =1.11 F ₅ as long as the desired thickness of material 110 matches the measured thickness.

Coating delivery system 160 of system 100 is any system capable of delivering material 110 to sprayer 130 . Coating delivery system 160 can be coupled to one or more components of system 100 . For example, coating delivery system 160 can be physically coupled to sprayer 130 . As another example, coating delivery system 160 can be incorporated into robot 120 . In certain embodiments, coating delivery system 160 comprises one or more computer systems (e.g., one or more computer systems programmed to deliver material 110 to one or more components of system 100 (e.g., sprayer 130)). For example, computer system 300).

A Human Machine Interface (HMI) 170 is any interface that facilitates interaction between a user and a machine. For example, HMI 170 can communicate computational flow to the user. In certain embodiments, HMI 170 is a software application embedded in robot 120 . In some embodiments, HMI 170 utilizes Equations 1 and/or 2 above to determine how much flow rate adjustment is required for the number of remaining passes to achieve the target nominal thickness of material 110. to calculate

FIG. 2 illustrates a method 200 for regulating material flow rates, according to certain embodiments. Method 200 begins at step 210 . At step 220, a spray gun coupled to the robot makes a first predetermined pass of material (eg, material 110) at a first flow rate (eg, F _n ) onto a substrate (eg, substrate 180). spray several times. Method 200 then proceeds to step 230 . At step 230, a measurement device (eg, measurement device 140) measures one or more properties of the material sprayed onto the substrate while the material is wet. For example, the measuring device can measure the reflectance of wet materials. As another example, the measurement device can measure time-of-flight measurements (eg, transmission and reception times of terahertz pulses).

At step 240 of method 200, a processor (eg, analyzer 150) may determine the thickness of the wet material based on one or more measured properties. The method 200 then proceeds to step 250 where the processor calculates a second flow rate required to achieve a cured thickness of material within a second predetermined number of passes. The processor calculates a first predetermined number of passes, an expected thickness of the wet material for one pass of the first predetermined number of passes, a specified thickness of the wet material, and a first flow rate (e.g., Equation 2) A second flow rate can be calculated based on . For example, a second flow rate (e.g., F _n+1 ) may be obtained by multiplying a first predetermined number of passes (e.g., ) by an expected thickness (e.g., t ₁ ) to obtain a first value, this first Divide the unity value by the specified thickness (e.g., t _n ) to obtain a second value, and multiply this second value to obtain a second flow rate (e.g., F _n+1 ). It can be calculated by multiplying by a first flow rate (eg, F _n ).

Method 200 then proceeds to step 260 . At step 260, the processor determines whether the calculated second flow rate is different than the first flow rate. If the calculated second flow rate differs from the first flow rate, method 200 proceeds to step 270, where the flow rate is adjusted by one or more components of the system (eg, system 100). After adjusting the first flow rate to the second flow rate, method 200 proceeds to step 280, where the sprayer (eg, sprayer 130) spreads the material onto the substrate at the calculated second flow rate. 2. Spray a predetermined number of passes. If the second flow rate is the same as the first flow rate, the flow rate is not adjusted and the method 200 proceeds to step 280, where the sprayer directs the material at the first flow rate onto the substrate for a second predetermined number of passes. spray. Method 200 ends at step 290 .

Method 200 may include more or fewer steps than those shown in FIG. For example, the method 200 determines a second thickness of the wet material after a second predetermined number of passes, adjusts the flow rate from the second flow rate to a third flow rate, and sprays the material at the third flow rate. It can further comprise spraying a third predetermined number of passes over the substrate. As another example, the method 200 can include prepping the substrate prior to spraying the material onto the substrate in a first predetermined number of passes.

FIG. 3 illustrates a computer system 300 that can be utilized with the system shown in FIG. 1, according to certain embodiments. One or more computer systems 300 perform one or more steps of one or more methods described or illustrated herein. In particular embodiments, one or more computer systems 300 provide the functionality described or illustrated herein. In certain embodiments, software running on one or more computer systems 300 performs one or more steps of one or more methods described or illustrated herein, or It provides the functionality described or illustrated herein. Particular embodiments include portions of one or more of one or more computer systems 300 . References herein to computer systems can encompass computing devices, and vice versa, where appropriate. Further, references to a computer system can encompass one or more computer systems, where appropriate.

This disclosure contemplates any suitable number of computer systems 300 . This disclosure contemplates computer system 300 taking any suitable physical form. By way of example, and not limitation, computer system 300 may be an embedded computer system, system-on-chip (SOC), single-board computer system (SBC) (e.g., computer-on-module (COM) or system-on-module (SBC)). SOM), desktop computer systems, laptop or notebook computer systems, interactive kiosks, mainframes, networks of computer systems, mobile phones, personal digital assistants (PDAs), servers, tablet computer systems, or any of these Combinations of two or more are possible. Where appropriate, computer system 300 may include one or more computer systems 300 and may be integrated or distributed, across multiple locations, across multiple machines, multiple It can span data centers or reside in a cloud that can include one or more cloud components in one or more networks. Where appropriate, one or more computer systems 300 can perform one or more of the one or more methods described or illustrated herein without substantial spatial or temporal constraints. steps can be performed. By way of example, and not limitation, one or more computer systems 300 may implement one or more steps of one or more methods described or illustrated herein in real-time or batch mode. can be run with One or more computer systems 300 may, where appropriate, perform one or more steps of one or more methods described or illustrated herein at different times or locations. can do.

In particular embodiments, computer system 300 includes processor 302 , memory 304 , storage device 306 , input/output (I/O) interface 308 , communication interface 310 , and bus 312 . Although this disclosure describes and illustrates a particular computer system having a particular number of particular components in a particular arrangement, this disclosure may include any suitable number of any suitable components in any suitable computer system. We envision any suitable computer system having in place.

In particular embodiments, processor 302 includes hardware for executing instructions, such as those that make up a computer program. By way of example, and not limitation, to execute instructions, processor 302 reads (or fetches) instructions from internal registers, internal cache, memory 304, or storage device 306 and decodes them. Execute, and then write one or more results to internal registers, internal cache, memory 304 , or storage 306 . In particular embodiments, processor 302 may include one or more internal caches for data, instructions, or addresses. This disclosure contemplates any suitable number of any suitable internal caches, where appropriate. By way of example, and not limitation, processor 302 may include one or more instruction caches, one or more data caches, and one or more translation lookaside buffers (TLBs). can be done. The instructions in the instruction cache can be copies of the instructions in memory 304 or storage 306, and the instruction cache can speed up retrieval of those instructions by processor 302. FIG. Data in the data cache may be data in memory 304 or storage 306 relating to instructions executing on processor 302 to operate, for access by subsequent instructions executing on processor 302, or for writing to memory 304 or storage 306. It may be the result of a previous instruction executed by processor 302, or other suitable copy of data. A data cache can speed up read or write operations by processor 302 . The TLB can speed up translation of virtual addresses for the processor 302 . In particular embodiments, processor 302 may include one or more internal registers for data, instructions, or addresses. This disclosure contemplates processor 302 including any suitable number of any suitable internal registers, where appropriate. Processor 302 may include one or more arithmetic logic units (ALUs), may be a multi-core processor, or may include one or more processors 302, where appropriate. Although this disclosure describes and illustrates a particular processor, it contemplates any suitable processor.

In particular embodiments, memory 304 includes main memory for storing instructions for processor 302 to execute or data for processor 302 to operate on. By way of example, and not limitation, computer system 300 may load instructions into memory 304 from storage device 306 or another source (eg, another computer system 300, etc.). Processor 302 may then load instructions from memory 304 into internal registers or an internal cache. To execute instructions, processor 302 may read instructions from internal registers or an internal cache and decode them. During or after execution of an instruction, processor 302 may write one or more results (which may be intermediate or final results) to internal registers or internal caches. Processor 302 can then write one or more of those results to memory 304 . In particular embodiments, processor 302 executes only instructions residing within one or more internal registers or internal caches, or residing within memory 304, within one or more internal registers or internal caches, or It operates only on data that is in memory 304 (as opposed to storage device 306, etc.). One or more memory buses (each including an address bus and a data bus) may couple processor 302 to memory 304 . Bus 312 may include one or more memory buses, as described below. In particular embodiments, one or more memory management units (MMUs) reside between processor 302 and memory 304 and facilitate processor 302 requested accesses to memory 304 . In particular embodiments, memory 304 includes random access memory (RAM). Where appropriate, this RAM may be volatile memory, and where appropriate, this RAM may be dynamic RAM (DRAM) or static RAM (SRAM). Moreover, where appropriate, this RAM may be single-ported or multi-ported RAM. This disclosure contemplates any suitable RAM. Memory 304 may include one or more memories 304, where appropriate. Although this disclosure describes and illustrates particular memories, this disclosure contemplates any suitable memory.

In particular embodiments, storage device 306 includes mass storage for data or instructions. By way of example, and not limitation, storage device 306 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or any of these. A combination of two or more of these may be included. Storage 306 may include removable or non-removable (or fixed) media, where appropriate. Storage 306 may be internal or external to computer system 300, where appropriate. In particular embodiments, storage device 306 is non-volatile solid-state memory. In particular embodiments, storage device 306 includes read-only memory (ROM). Where appropriate, this ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically erasable programmable ROM (EAROM), or flash memory; Combinations of two or more of these are possible. This disclosure contemplates mass storage device 306 taking any suitable physical form. Storage device 306 may, where appropriate, include one or more storage control units that facilitate communication between processor 302 and storage device 306 . Storage device 306 may include one or more storage devices 306, where appropriate. Although this disclosure describes and illustrates particular storage devices, this disclosure contemplates any suitable storage devices.

In particular embodiments, I/O interface 308 (e.g., interface 256) provides one or more interfaces for communication between computer system 300 and one or more I/O devices. Includes hardware, software, or both. Computer system 300 may include one or more of these I/O devices, where appropriate. One or more of these I/O devices enable communication between humans and computer system 300 . By way of example, but not limitation, I/O devices include keyboards, keypads, microphones, monitors, mice, printers, scanners, speakers, still cameras, styluses, tablets, touch screens, trackballs, video cameras, Other suitable I/O devices, or combinations of two or more of these, may be included. An I/O device may include one or more sensors. This disclosure contemplates any suitable I/O devices and any suitable I/O interfaces to them. Where appropriate, I/O interface 308 may include one or more device or software drivers that enable processor 302 to drive one or more of these I/O devices. can. I/O interfaces 308 may include one or more I/O interfaces 308, where appropriate. Although this disclosure describes and illustrates particular I/O interfaces, this disclosure contemplates any suitable I/O interfaces.

In particular embodiments, communication interface 310 (eg, interface 256) provides communication (eg, packet-based communication) between computer system 300 and one or more other computer systems 300 or one or more networks communication, etc.), including hardware, software, or both that provide one or more interfaces. By way of example, and not limitation, communication interface 310 may include a network interface controller (NIC) or network adapter for communication with an Ethernet or other wireline-based network, or a network such as a WI-FI network. A wireless NIC (WNIC) or wireless adapter may be included for communication with a wireless network. This disclosure contemplates any suitable network and any suitable communication interface 310 thereto. By way of example, and not limitation, computer system 300 may be connected to an ad hoc network, a personal area network (PAN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), or the Internet. It can communicate with one or more parts, or a combination of two or more of these. One or more portions of one or more of these networks may be wired or wireless. As an example, the computer system 300 may be a wireless PAN (WPAN) (eg, BLUETOOTH WPAN), a WI-FI network, a WI-MAX network, a mobile phone network (eg, Global System for Mobile Communications (GSM) (trademark)) network), or other suitable wireless network, or a combination of two or more of these. Computer system 300 may include any suitable communication interface 310 to any of these networks, where appropriate. Communication interface 310 may include one or more communication interfaces 310, where appropriate. Although this disclosure describes and illustrates a particular communication interface, this disclosure contemplates any suitable communication interface.

In particular embodiments, bus 312 includes hardware, software, or both connecting components of computer system 300 to each other. By way of example, and not limitation, bus 312 may be an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport ( HT) Interconnect, Industry Standard Architecture (ISA) Bus, InfiniBand Interconnect, Low Pin Count (LPC) Bus, Memory Bus, Micro Channel Architecture (MCA) Bus, Peripheral Component Interconnect (PCI) Bus, PCI Express (PCIe) Bus , a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or another suitable bus or a combination of two or more of these. Bus 312 may include one or more buses 312, where appropriate. Although this disclosure describes and illustrates particular buses, this disclosure contemplates any suitable buses or interconnects.

Components of computer system 300 may be integrated or separated. In certain embodiments, each component of computer system 300 may be housed within a single chassis. The operations of computer system 300 may be performed by more, fewer, or other components. Additionally, operations of computer system 300 may be performed using any suitable logic circuitry, which may comprise software, hardware, other logic circuitry, or any suitable combination of the foregoing. .

As used herein, a computer-readable non-transitory storage medium or media, where appropriate, includes one or more semiconductor-based or other integrated circuits (ICs) such as Field Programmable Gate Arrays (FPGAs) or application specific IC (ASIC), hard disk drive (HDD), hybrid hard drive (HHD), optical disk, optical disk drive (ODD), magneto-optical disk, magneto-optical drive, floppy disk, floppy disk drive (FDD), magnetic may include tapes, solid state drives (SSDs), RAM drives, secure digital cards or drives, any other suitable computer readable non-transitory storage media, or any suitable combination of two or more of these. can. Computer-readable non-transitory storage media may, where appropriate, be volatile, non-volatile, or a combination of volatile and non-volatile.

In this specification, "or" is inclusive and not exclusive, unless expressly meant otherwise or the context dictates otherwise. Thus, as used herein, "A or B" means A, B, or both, unless expressly meant otherwise or the context dictates otherwise. Further, "and" is both conjunctive and concurrent, unless expressly meant otherwise or the context dictates otherwise. Thus, as used herein, "A and B" means "A and B in combination or together," unless expressly meant otherwise or the context indicates otherwise.

The scope of this disclosure encompasses all changes, substitutions, variations, alterations, and modifications to the example embodiments described or illustrated herein that a person skilled in the art would comprehend. The scope of this disclosure is not limited to the exemplary embodiments described or illustrated herein. Further, although the disclosure herein describes and describes each embodiment as including particular components, elements, functions, acts, or steps, any of these embodiments may Any combination or permutation of components, elements, functions, acts or steps described or illustrated anywhere in the specification may be included and will be understood by a person skilled in the art. Moreover, any attachment to a device or system or component of a device or system that is adapted, arranged, capable, configured, enabled, operable, or operative to perform a specified function References in the claims refer to the specific It encompasses the device, system, or component regardless of whether the feature is activated, turned on, or unlocked.

100 system 110 material 120 robot 130 sprayer 140 measuring device 150 analyzer 160 coating delivery system 170 HMI
180 base material

Claims (17)

robot and
a sprayer coupled to the robot and operable to spray material at a first flow rate onto a substrate for a first predetermined number of passes;
a measuring device operable to measure one or more properties of the material, including reflectance, while the material is sprayed onto the substrate while in a wet state;
an analyzer;
A system comprising
The analyzer is
determining the thickness of the wet material based on the one or more measured properties;
operable to calculate a second flow rate required to obtain a certain cured thickness of said material within a second predetermined number of passes, said calculated second flow rate being:
the first predetermined number of passes; and
an expected thickness of the wet material for one pass of the first predetermined number of passes;
the determined thickness of the wetting material;
Based on the first flow rate and
Calculating the second flow rate comprises:
multiplying the first predetermined number of passes by the expected thickness to obtain a first value;
dividing the first value by the determined thickness to obtain a second value;
multiplying the second value by the first flow rate to obtain the second flow rate;
including,
A system characterized by: 2. The system of claim 1, wherein the measuring device is a microwave probe and the one or more measured properties are one or more electrical properties. 2. The system of claim 1, wherein the measurement device is a terahertz sensor and the one or more measured properties are one or more time-of-flight measurements. 2. The system of claim 1, wherein said first flow rate and said second flow rate are equal. 2. The method of claim 1, wherein the material is paint, and wherein the sprayer is further operable to spray the material at a calculated second flow rate onto the substrate for the second predetermined number of passes. system. 2. The system of claim 1, wherein the measuring device operates to measure the one or more properties of the wet material without contacting the wet material. spraying material at a first flow rate onto the substrate for a first predetermined number of passes with a sprayer coupled to the robot;
measuring, with a measuring device, one or more properties of the material, including reflectance, while the material is in a wet state, sprayed onto the substrate;
determining, with an analyzer, the thickness of the wet material based on the one or more measured properties;
calculating, with the analyzer, a second flow rate required to obtain a cured thickness of the material within a second predetermined number of passes;
a method comprising
The calculated second flow rate is
the first predetermined number of passes; and
an expected thickness of the wet material for one pass of the first predetermined number of passes;
the determined thickness of the wetting material;
Based on the first flow rate and
Calculating the second flow rate comprises:
multiplying the first predetermined number of passes by the expected thickness to obtain a first value;
dividing the first value by the specified thickness to obtain a second value;
multiplying the second value by the first flow rate to obtain the second flow rate;
including,
A method characterized by: 8. The method of claim 7 , wherein the measuring device is a microwave probe and the one or more measured properties are one or more electrical properties. 8. The method of claim 7 , wherein the measurement device is a terahertz sensor and the one or more measured properties are one or more time-of-flight measurements. 8. The method of claim 7 , wherein said first flow rate and said second flow rate are equal. 8. The method of claim 7 , further comprising spraying the material with the sprayer at a calculated second flow rate onto the substrate for the second predetermined number of passes, wherein the material is paint. . 8. The method of claim 7 , wherein the measuring device measures the one or more properties of the wetting material without contacting the wetting material. robot and
a sprayer coupled to the robot and operable to spray material at a first flow rate onto a substrate for a first predetermined number of passes;
one or more computer processors;
A device comprising
The one or more computer processors are
data captured by a measurement device while the material was wet, including one or more properties of the material sprayed onto the substrate by the sprayer during a first predetermined number of passes; and wherein the one or more measured properties include reflectance;
determining the thickness of the wet material based on the one or more measured properties;
configured to calculate a second flow rate required to obtain a cured thickness of said material within a second predetermined number of passes, said calculated second flow rate being:
the first predetermined number of passes; and
an expected thickness of the wet material for one pass of the first predetermined number of passes;
the determined thickness of the wetting material;
Based on the first flow rate and
Calculating the second flow rate comprises:
multiplying the first predetermined number of passes by the expected thickness to obtain a first value;
dividing the first value by the determined thickness to obtain a second value;
multiplying the second value by the first flow rate to obtain the second flow rate;
including,
A device characterized by: 14. The apparatus of claim 13, wherein said measuring device is a microwave probe and said one or more measured properties are one or more electrical properties. 14. The apparatus of claim 13 , wherein said measuring device is a terahertz sensor and said one or more measured properties are one or more time-of-flight measurements. 14. The apparatus of claim 13 , wherein said first flow rate and said second flow rate are equal. The one or more computer processors provide one or more instructions to the sprayer to spray the material at the predicted second flow rate onto the substrate for the second predetermined number of passes. 14. The apparatus of claim 13 , further configured to provide a

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